RESTORATION OF SPATIALLY INHOMOGENEOUS IMAGES BASED ON A DOUBLY STOCHASTIC MODEL
N. A. Andriyanov1, K. K. Vasiliev2, V. E. Dementiev2, A. V. Belyanchikov2
1Financial University under the Government of the Russian Federation, Moscow, Russia
2Ulyanovsk State Technical University, Ulyanovsk, Russia
Keywords: image processing, doubly stochastic models, nonlinear filtering, image recovery
Abstract
The article deals with the issues of image restoration when only a part of observations subjected to additive noise regularly placed in the original image is available. In other words, the problem of restoration of a thinned image is solved (based on pilot pixels). Pixels themselves are mixed with the white Gaussian noise. To solve this problem, special modifications of nonlinear filters are synthesized based on deep doubly stochastic Gaussian models. The results obtained allow us to draw a conclusion about the effectiveness of the proposed filters in comparison with linear methods and traditional algorithms. The study shows that images can be reconstructed based on only 50% of information using a doubly stochastic model, resulting in a relative error of only 9%.
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